The large‐scale irrigation is demonstrated to significantly affect regional hydroclimatic regime by changing underlying surface (e.g., crop growth and soil moisture), yet the contribution of ...irrigation‐induced crop “greening” to climatic effects is not well understood. In this study, we use a window‐searching algorithm to evaluate the irrigation effects on vegetation with leaf area index (LAI) as a vegetation index, and further conduct three regional climate simulations to investigate the comprehensive effects of irrigation on surface fluxes and local climate over the North China Plain. We find that irrigation leads to a more significant greening in March‐May (MAM) than in June‐September (JJAS). Especially in April and May, the irrigation‐induced change in LAI (ΔLAI) exceeds 0.4 m2 m−2 in intensively irrigated areas. Irrigation induces a cooling effect in air temperature at 2 m with decreasing magnitudes of 0.58°C in MAM and 0.43°C in JJAS, respectively, in which ΔLAI contributes about 34.5% (0.20°C) and 14.0% (0.06°C). Likewise, the irrigation‐induced changes in latent heat flux, sensible heat flux, and transpiration are all enlarged via the irrigation greening effect. Whereas the increase in soil evaporation is alleviated, because the greening‐triggered enhancement of crop root uptake reduces the increase in soil moisture. Moreover, irrigation effects on net radiation depend on the competing influences of irrigation‐triggered cooling and cloud formation. This study provides beneficial references to understand the impact of irrigation on regional energy balance and water cycle, and highlights that in modeling hydroclimatic feedback to irrigation, the greening effect induced by irrigation should be considered.
Key Points
Irrigation greening effect over the North China Plain is quantified using a window‐searching algorithm with leaf area index (LAI) as a vegetation index
Irrigation‐induced change in LAI contributes about 34.5% and 14.0% of irrigation cooling effects in March‐May and June‐September
Irrigation effect on net radiation depends on the competing influences of irrigation‐triggered cooling and cloud formation
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•The increase of the polymeric molecular weight decreased hydrophilicity, surface hardness, mechanical properties, and crystallinity.•No significant crystallinity changes were ...observed during the degradation process.•Fiber diameter, porosity, and mass loss linearly decreased with the degradation time, while compressive modulus and strength decreased non-linearly.•Enhanced in vitro hADSC proliferation and osteogenic differentiation were observed on lower molecular weight PCL scaffolds.
Polycaprolactone (PCL) is one of the most recognized polymeric materials used for bone tissue engineering scaffold fabrication. This study aims to evaluate the effects of the molecular weight (Mn) of PCL on the degradation kinematics, surface, microstructural, thermal, mechanical, and biological properties of 3D printed bone scaffolds. Surface properties were investigated considering water-in-air contact angle and nanoindentation tests, while morphological characteristics and degradation kinematics (accelerated degradation tests) were examined using scanning electron microscopy (SEM), pairing with thermal and mechanical properties monitored at each considered time point. A set of mathematical equations describing the variation of fiber diameter, porosity, mechanical properties, and weight, as a function of molecular weight and degradation time, were obtained based on the experimental results. Human adipose-derived stem cells (hADSCs) proliferation and differentiation tests were also conducted using in vitro colorimetric assay. All results indicated that molecular weight had impacts on the surface, mechanical and biological properties of PCL scaffolds, while no significant effects were observed on the degradation rate. Scaffolds with lower molecular weight presented better bio-mechanical properties. These findings provide useful information for the design of polymeric bone tissue engineering scaffolds.
•AWSI based on blue-green water and water footprint (WF) framework is established.•Blue water dominates in water resources while blue WF accounts for 12.7% of the total.•Water scarcity was aggravated ...from 1999 to 2014 in agricultural production of China.•The AWSI is suitable for water scarcity evaluations, particularly in arid area.
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An indicator, agricultural water stress index (AWSI), was established based blue-green water resources and water footprint framework for regional water scarcity in agricultural production industry evaluation. AWSI is defined as the ratio of the total agricultural water footprint (AWF) to water resources availability (AWR) in a single year. Then, the temporal and spatial patterns of AWSI in China during 1999–2014 were analyzed based on the provincial AWR and AWF quantification. The results show that the annual AWR in China has been maintained at approximately 2540Gm3, of which blue water accounted for >70%. The national annual AWF was approximately 1040Gm3 during the study period and comprised 65.6% green, 12.7% blue and 21.7% grey WFs The space difference in both the AWF for per unit arable land (AWFI) and its composition was significant. National AWSI was calculated as 0.413 and showed an increasing trend in the observed period. This index increased from 0.320 (mid-water stress level) in 2000 to 0.490 (high water stress level) in the present due to the expansion of the agricultural production scale. The Northern provinces, autonomous regions and municipalities (PAMs) have been facing high water stress, particularly the Huang-Huai-Hai Plain, which was at a very high water stress level (AWSI>0.800). Humid South China faces increasingly severe water scarcity, and most of the PAMs in the region have converted from low water stress level (AWSI=0.100–0.200) to mid water stress level (AWSI=0.200–0.400). The AWSI is more appropriate for reflecting the regional water scarcity than the existing water stress index (WSI) or the blue water scarcity (BWS) indicator, particularly for the arid agricultural production regions due to the revealed environmental impacts of agricultural production. China should guarantee the sustainable use of agricultural water resources by reducing its crop water footprint.
•Estimate the single empirical dimensionless parameter in Budyko-type equation.•Identify dominant interactions of influencing factors through MARS model.•Emphasis the impact of agricultural ...activities on water availability assessment.
Quantifying precipitation (P) partition into evapotranspiration (E) and runoff (Q) is of great importance for global and regional water availability assessment. Budyko framework serves as a powerful tool to make simple and transparent estimation for the partition, using a single parameter, to characterize the shape of the Budyko curve for a “specific basin”, where the single parameter reflects the overall effect by not only climatic seasonality, catchment characteristics (e.g., soil, topography and vegetation) but also agricultural activities (e.g., cultivation and irrigation). At the regional scale, these influencing factors are interconnected, and the interactions between them can also affect the single parameter of Budyko-type equations’ estimating. Here we employ the multivariate adaptive regression splines (MARS) model to estimate the Budyko curve shape parameter (n in the Choudhury’s equation, one form of the Budyko framework) of the selected 96 catchments across China using a data set of long-term averages for climatic seasonality, catchment characteristics and agricultural activities. Results show average storm depth (ASD), vegetation coverage (M), and seasonality index of precipitation (SI) are three statistically significant factors affecting the Budyko parameter. More importantly, four pairs of interactions are recognized by the MARS model as: The interaction between CA (percentage of cultivated land area to total catchment area) and ASD shows that the cultivation can weaken the reducing effect of high ASD (>46.78 mm) on the Budyko parameter estimating. Drought (represented by the value of Palmer drought severity index < -0.74) and uneven distribution of annual rainfall (represented by the value of coefficient of variation of precipitation > 0.23) tend to enhance the Budyko parameter reduction by large SI (>0.797). Low vegetation coverage (34.56%) is likely to intensify the rising effect on evapotranspiration ratio by IA (percentage of irrigation area to total catchment area). The Budyko n values estimated by the MARS model reproduce the calculated ones by the observation well for the selected 96 catchments (with R = 0.817, MAE = 4.09). Compared to the multiple stepwise regression model estimating the parameter n taken the influencing factors as independent inputs, the MARS model enhances the capability of the Budyko framework for assessing water availability at regional scale using readily available data.
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•Carbon sink flux via rock chemical weathering in the Tibetan Plateau accounted for 23% of that in China.•Carbon sink flux via rock chemical weathering in the polar zone is more ...pronounced than that in the arid region, warm temperate zone, and cool temperate zone over the Tibetan Plateau.•Carbon sink flux via rock chemical weathering in the Tibetan Plateau showed a decreasing trend from 2000 to 2017 under climate warming.
Chemical weathering of rocks plays an important role in the global carbon cycle. The Tibetan Plateau (TP), known as “the Asian Water Tower”, is highly sensitive to climate change. Therefore, the impacts of climate change on rates of carbon sink via chemical weathering of rocks (RWCSR) and carbon sink flux via rock chemical weathering (RWCSF) in the TP must be understood and quantified. In this study, we assessed the RWCSR and RWCSF in the TP within China from 2000 to 2017 based on high-precision hydrometeorological data (2000–2017) and the Global Erosion Model for CO2 fluxes (GEM-CO2 model). The multi-year average RWCSR in the TP is 1.35 × 105 ± 2.11 × 105 mol/km2. The RWCSR in most regions of the TP remained constant from 2000 to 2017. From 2000 to 2017, the RWCSF in the TP was between 263.39 × 109 and 380.45 × 109 mol/yr, with an average of 338.37 × 109 mol/yr, which accounted for 23 % of the RWCSF in China and 1 % of the RWCSF in the globe. Under climate warming, the RWCSF in the TP showed a decreasing trend from 2000 to 2017. The relative contribution rates of runoff, precipitation, and land surface temperature to the change in RWCSR reached 49.26 %, 38.86 %, and 10.49 %, respectively. This study explored the applicability of the GEM-CO2 model to the TP and provided a scientific basis for assessing the impact of climate change on carbon sink via chemical weathering of rocks in the TP.
Objective To establish a systematic registry of aortic dissection in China, assess the clinical features of Chinese patients with acute aortic dissection (AAD), and compare our results with the data ...published by the International Registry of Acute Aortic Dissection (IRAD). Methods We established the first Registry of Aortic Dissection in China (Sino-RAD) in 2011. Then we evaluated 1003 patients with AAD in Sino-RAD and compared our results with those reported by IRAD. Results Compared with IRAD, the patients with AAD in Sino-RAD were significantly younger. Also, the ratio of male patients in Sino-RAD was significantly greater for the total cohort and the type A and B cohorts. The overall in-hospital mortality was 10.3% in Sino-RAD. For type A dissection, more patients in Sino-RAD received medical treatment and fewer received surgical treatment. The overall mortality, mortality of medical treatment, and mortality of surgical treatment was lower in Sino-RAD. In type B dissection, fewer patients in Sino-RAD received medical and surgical treatment and more received endovascular treatment. Conclusions The first Sino-RAD, including 15 large cardiovascular centers throughout China, was established. Our data were compared with those reported by IRAD. We found that, compared with Western populations, Chinese patients with AAD showed 6 differences, including earlier onset, more male patients, a low incidence of hypertension, a low incidence of chest pain, a high incidence of back pain, great differences in the choice of therapeutic strategies, and relatively low in-hospital mortality.
•Analyze the uncertainties in ET0 projection from estimation method and data quality.•Provide reliable future projection of ET0 from GCMs.•Discuss the implication of future ET0 change to regional ...water resources.
As the indicator of atmospheric evaporative demand over a hypothetical reference surface, reference evapotranspiration (ET0) is an important input to hydrological models. Future projections of ET0 are of great importance in assessing the potential impacts of climate change on the hydrologic regime as well as water resources systems. Different estimating formulations and different input data reliabilities existing in practice determine there may be potential uncertainty in projection of future ET0 change. Here we investigated the difference of future ET0 response to climate change based on three approaches, i.e., more physically based Penman–Montieth equation with relatively uncertain downscaled data quality, more empirical temperature-based Hargreaves equation with more reliable downscaled input data, and statistical downscaling method with directly selecting ET0 as predictands. The Hanjiang River Basin, a headwater source of famous South to North Water Diversion Project (SNWDP) in China was chosen as example to illustrate this issue. Although similar increase processes of ET0 in the Hanjiang River Basin were suggested by three methods, the magnitude of ET0 increase differs substantially, indicating that uncertainty still exist despite of approximate performance of these methods in simulating general trends. Whilst increasing aridity index and decreasing water surplus over the period of 2011–2099 would inevitably cause negative impacts on the implementation of the SNWDP and effective adapting measures are thus expected.
Irrigation has distinct impacts on extreme temperatures. Due to the carryover effect of soil moisture into other seasons, temperature impacts of irrigation are not limited to irrigated seasons. ...Focusing on the North China Plain, where irrigation occurs in both spring (March‐April‐May) and summer (June‐July‐August), with a higher proportion of irrigation water applied during spring, we investigate the impact of spring irrigation on summer extreme heat events. Based on partial correlation analysis of data products, we find positive correlations between spring and summer soil moisture, suggesting that spring irrigation‐induced water surplus persists into the following summer and affects regional climate by impacting surface energy partitioning. Regional climate simulations confirm cross‐seasonal climatic effects and show that spring irrigation reduces the frequency and intensity of summer extreme heat events by approximately −2.5 days and −0.29°C, respectively. Our results highlight the importance of the cross‐seasonal climatic effect of irrigation in mitigating climate extremes.
Plain Language Summary
Irrigation exerts a stronger impact on extreme temperatures than on mean temperatures. The North China Plain (NCP) is a typical winter wheat‐summer maize rotation planting area, where irrigation is necessary in both spring and summer, but with a higher proportion of irrigation water applied during spring. The climatic effects of spring and summer irrigation in the NCP are intertwined due to the carryover effects of soil moisture. Recently, the climatic effect of irrigation in the NCP has been extensively explored, whereas the cross‐seasonal effects of irrigation on summer extreme heat events have never been quantified. In this study, we employ the Weather Research and Forecasting model coupled with a demand‐driven irrigation algorithm to discern the effects of spring and/or summer irrigation on summer extreme heat events by means of idealized climate simulations. The results show that spring and summer irrigation significantly reduces the frequency and intensity of summer extreme heat events by approximately −6.5 days and −1.0°C, of which spring irrigation contributes about 38% and 30%, respectively. Our findings underline the importance of irrigation‐induced climate impacts in mitigating extreme heat events and emphasize that climate change adaptation planning in terms of irrigation must account for cross‐seasonal climatic effects.
Key Points
Effect of multi‐seasonal irrigation on summer extreme heat events is investigated
Spring irrigation is beneficial for reducing summer extreme heat events
Irrigation modulates the relationship between spring and summer soil moisture
•Temporal variations of model parameters have significant correlations with precipitation and vegetation.•A method is developed to downscale mean annual parameter to monthly time-variant ...parameters.•Time-variant parameters improve the performance of monthly runoff modeling.
The temporal variation of model parameters is affected by the catchment conditions and has a significant impact on hydrological simulation. This study aims to evaluate the seasonality and downscaling of model parameter across time scales based on monthly and mean annual water balance models with a common model framework. Two parameters of the monthly model, i.e., k and m, are assumed to be time-variant at different months. Based on the hydrological data set from 121 MOPEX catchments in the United States, we firstly analyzed the correlation between parameters (k and m) and catchment properties (NDVI and frequency of rainfall events, α). The results show that parameter k is positively correlated with NDVI or α, while the correlation is opposite for parameter m, indicating that precipitation and vegetation affect monthly water balance by controlling temporal variation of parameters k and m. The multiple linear regression is then used to fit the relationship between ε and the means and coefficient of variations of parameters k and m. Based on the empirical equation and the correlations between the time-variant parameters and NDVI, the mean annual parameter ε is downscaled to monthly k and m. The results show that it has lower NSEs than these from model with time-variant k and m being calibrated through SCE-UA, while for several study catchments, it has higher NSEs than that of the model with constant parameters. The proposed method is feasible and provides a useful tool for temporal scaling of model parameter.
Irrigation over the North China Plain (NCP) has been demonstrated to lower temperature by altering the surface energy budget. During past decades, the concurrence of irrigated area variation and ...reduced irrigation intensity prompted our investigation into whether there has been a temporal change in irrigation cooling effect over the NCP, which is largely unknown. Using historical observations in 1979–2018, we detect a shift in the cooling effect occurring around 1995, when the expansion of irrigated area was going to slow down and water‐conserving irrigation technology was boomingly introduced. After this time, the accelerated process of cooling effect (−0.0045°C year−1) switches to a decelerated one (0.0089°C year−1). Regional climate simulations also show a pronounced slowdown in irrigation‐induced cooling with the rate of 0.0081°C year−1. The irrigation‐induced cooling is expected to be weaker with the persistent reduction in agricultural water use and contribute to a more rapid warming.
Plain Language Summary
The North China Plain is the largest irrigated area in China. However, the irrigated agriculture situation in this fertile plain has been going through moderated expansion of irrigated area and reduced irrigation intensity. The variations in irrigation‐induced cooling effect along with this irrigation development were thus investigated based on in situ observations and model simulations. The combined analysis clearly supports a shift from enhancement to alleviation in cooling effect during past decades. The slowdown of irrigation feedback is therefore likely to enable more rapid warming in the future.
Key Points
The local cooling effect of irrigation during past decades is evaluated in observations and model simulations
Over the North China Plain, the irrigation‐induced cooling effect has decreased since the mid‐1990s
Persistent changes in irrigation water use cannot be overlooked in climate attribution studies
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